The properties of early-type galaxies in the Ursa Major cluster

Using SDSS-DR7 and NASA/IPAC Extragalactic Database spectroscopic data, we identify 166 galaxies as members of the Ursa Major cluster with Mr < -13.5 mag. We morphological classify all galaxies by means of carefully inspecting g-, r-, i-band colour and monochromatic images. We show that the Ursa Major cluster is dominated by late-type galaxies, but also contains a significant number of early- type galaxies, particularly in the dwarf regime. We present further evidence for the existence of several subgroups in the cluster, consistent with previous findings. The early-type fraction is found to correlate with the mass of the subgroup. We also investigate environmental effects by comparing the properties of the Ursa Major early-type dwarf galaxies to those of the Virgo cluster. In contrast to the Virgo, the red sequence of the Ursa Major cluster is only sparsely populated in the optical and ultraviolet colour-magnitude relations. It also shows a statistically significant gap between -18 < Mr < -17 mag, i.e. the Ursa Major cluster lacks early-type dwarf galaxies at the bright end of their luminosity function. We discover that the majority of early-type dwarf galaxies in the Ursa Major cluster have blue cores with hints of recent or ongoing star formation. We suggest that gravitational tidal interactions can trigger central blue star forming regions in early-type dwarfs. After that, star formation would only fade completely when the galaxies experience ram pressure stripping or harassment, both of which are nearly absent in the Ursa Major cluster.Comment: 19 pages, 18 figures, 2 tables, Accepted for publication in MNRA

The Extended Virgo Cluster Catalog

We present a new catalog of galaxies in the wider region of the Virgo cluster, based on the Sloan Digital Sky Survey (SDSS) Data Release 7. The Extended Virgo Cluster Catalog (EVCC) covers an area of 725 deg^2 or 60.1 Mpc^2. It is 5.2 times larger than the footprint of the classical Virgo Cluster Catalog (VCC) and reaches out to 3.5 times the virial radius of the Virgo cluster. We selected 1324 spectroscopically targeted galaxies with radial velocities less than 3000 kms^-1. In addition, 265 galaxies that have been missed in the SDSS spectroscopic survey but have available redshifts in the NASA Extragalactic Database are also included. Our selection process secured a total of 1589 galaxies of which 676 galaxies are not included in the VCC. The certain and possible cluster members are defined by means of redshift comparison with a cluster infall model. We employed two independent and complementary galaxy classification schemes: the traditional morphological classification based on the visual inspection of optical images and a characterization of galaxies from their spectroscopic features. SDSS u, g, r, i, and z passband photometry of all EVCC galaxies was performed using Source Extractor. We compare the EVCC galaxies with the VCC in terms of morphology, spatial distribution, and luminosity function. The EVCC defines a comprehensive galaxy sample covering a wider range in galaxy density that is significantly different from the inner region of the Virgo cluster. It will be the foundation for forthcoming galaxy evolution studies in the extended Virgo cluster region, complementing ongoing and planned Virgo cluster surveys at various wavelengths.Comment: 69 pages, 29 figures, 4 tables, accepted for publication in the ApJ

Factors Associated with Continuous Use of a Cancer Education Metaverse Platform: Mixed Methods Study

Background: Early detection of cancer and provision of appropriate treatment can increase the cancer cure rate and reduce cancer-related deaths. Early detection requires improving the cancer screening quality of each medical institution and enhancing the capabilities of health professionals through tailored education in each field. However, during the COVID-19 pandemic, regional disparities in educational infrastructure emerged, and educational accessibility was restricted. The demand for remote cancer education services to address these issues has increased, and in this study, we considered medical metaverses as a potential means of meeting these needs. In 2022, we used Metaverse Educational Center, developed for the virtual training of health professionals, to train radiologic technologists remotely in mammography positioning. Objective: This study aims to investigate the user experience of the Metaverse Educational Center subplatform and the factors associated with the intention for continuous use by focusing on cases of using the subplatform in a remote mammography positioning training project. Methods: We conducted a multicenter, cross-sectional survey between July and December 2022. We performed a descriptive analysis to examine the Metaverse Educational Center user experience and a logistic regression analysis to clarify factors closely related to the intention to use the subplatform continuously. In addition, a supplementary open-ended question was used to obtain feedback from users to improve Metaverse Educational Center. Results: Responses from 192 Korean participants (male participants: n=16, 8.3%; female participants: n=176, 91.7%) were analyzed. Most participants were satisfied with Metaverse Educational Center (178/192, 92.7%) and wanted to continue using the subplatform in the future (157/192, 81.8%). Less than half of the participants (85/192, 44.3%) had no difficulty in wearing the device. Logistic regression analysis results showed that intention for continuous use was associated with satisfaction (adjusted odds ratio 3.542, 95% CI 1.037-12.097; P=.04), immersion (adjusted odds ratio 2.803, 95% CI 1.201-6.539; P=.02), and no difficulty in wearing the device (adjusted odds ratio 2.020, 95% CI 1.004-4.062; P=.049). However, intention for continuous use was not associated with interest (adjusted odds ratio 0.736, 95% CI 0.303-1.789; P=.50) or perceived ease of use (adjusted odds ratio 1.284, 95% CI 0.614-2.685; P=.51). According to the qualitative feedback, Metaverse Educational Center was useful in cancer education, but the experience of wearing the device and the types and qualities of the content still need to be improved. Conclusions: Our results demonstrate the positive user experience of Metaverse Educational Center by focusing on cases of using the subplatform in a remote mammography positioning training project. Our results also suggest that improving users’ satisfaction and immersion and ensuring the lack of difficulty in wearing the device may enhance their intention for continuous use of the subplatform

Neutrino mass and low-scale leptogenesis in a testable SUSY SO(10) model

It is shown that a supersymmetric SO(10) model extended with fermion singlets can accommodate the observed neutrino masses and mixings as well as generate the desired lepton asymmetry in concordance with the gravitino constraint. A necessary prediction of the model is near-TeV scale doubly-charged Higgs scalars which should be detectable at the LHC.Comment: Latex, 7 pages, 2 figures, minor clarifications added, to appear in Physics Letters

Supramolecular Enhancement of Electrochemical Nitrate Reduction Catalyzed by Cobalt Porphyrin Organic Cages for Ammonia Electrosynthesis in Water.

The electrochemical nitrate (NO3 - ) reduction reaction (NO3 RR) to ammonia (NH3 ) represents a sustainable approach for denitrification to balance global nitrogen cycles and an alternative to traditional thermal Haber-Bosch processes. Here, we present a supramolecular strategy for promoting NH3 production in water from NO3 RR by integrating two-dimensional (2D) molecular cobalt porphyrin (CoTPP) units into a three-dimensional (3D) porous organic cage architecture. The porphyrin box CoPB-C8 enhances electrochemical active site exposure, facilitates substrate-catalyst interactions, and improves catalyst stability, leading to turnover numbers and frequencies for NH3 production exceeding 200,000 and 56 s-1 , respectively. These values represent a 15-fold increase in NO3 RR activity and 200-mV improvement in overpotential for the 3D CoPB-C8 box structure compared to its 2D CoTPP counterpart. Synthetic tuning of peripheral alkyl substituents highlights the importance of supramolecular porosity and cavity size on electrochemical NO3 RR activity. These findings establish the incorporation of 2D molecular units into 3D confined space microenvironments as an effective supramolecular design strategy for enhancing electrocatalysis

Discovery of a large-scale H I plume in the NGC 7194 Group

We present the discovery of a new H I structure in the NGC 7194 group from the observations using the Karl G. Jansky Very Large Array. NGC 7194 group is a nearby (z ~ 0.027) small galaxy group with five quiescent members. The observations reveal a 200 kpc-long H I plume that spans the entire group with a total mass of M$_{HI}$ = 3.4 x 10$^{10}$ M$_{\odot}$. The line-of-sight velocity of the H I gas gradually increases from south (7200 km s$^{-1}$) to north (8200 km $^{-1}$), and the local velocity dispersion is up to 70 km s$^{-1}$. The structure is not spatially coincident with any member galaxies but it shows close associations with a number of blue star-forming knots. Intragroup H I gas is not rare, but this particular structure is still one of the unusual cases in the sense that it does not show any clear connection with sizable galaxies in the group. We discuss the potential origins of this large-scale H I gas in the NGC 7194 group and its relation with the intergalactic star-forming knots. We propose that this HI feature could have originated from tidal interactions among group members or the infall of a late-type galaxy into the group. Alternatively, it might be leftover gas from flyby intruders.Comment: 9 pages, 3 figure

Detection of PIWI and piRNAs in the mitochondria of mammalian cancer cells

AbstractPiwi-interacting RNAs (piRNAs) are 26–31 nt small noncoding RNAs that are processed from their longer precursor transcripts by Piwi proteins. Localization of Piwi and piRNA has been reported mostly in nucleus and cytoplasm of higher eukaryotes germ-line cells, where it is believed that known piRNA sequences are located in repeat regions of nuclear genome in germ-line cells. However, localization of PIWI and piRNA in mammalian somatic cell mitochondria yet remains largely unknown. We identified 29 piRNA sequence alignments from various regions of the human mitochondrial genome. Twelve out 29 piRNA sequences matched stem-loop fragment sequences of seven distinct tRNAs. We observed their actual expression in mitochondria subcellular fractions by inspecting mitochondrial-specific small RNA-Seq datasets. Of interest, the majority of the 29 piRNAs overlapped with multiple longer transcripts (expressed sequence tags) that are unique to the human mitochondrial genome. The presence of mature piRNAs in mitochondria was detected by qRT-PCR of mitochondrial subcellular RNAs. Further validation showed detection of Piwi by colocalization using anti-Piwil1 and mitochondria organelle-specific protein antibodies

The development of a web-based app employing machine learning for delirium prevention in long-term care facilities in South Korea

Background Long-term care facilities (LCFs) in South Korea have limited knowledge of and capability to care for patients with delirium. They also often lack an electronic medical record system. These barriers hinder systematic approaches to delirium monitoring and intervention. Therefore, this study aims to develop a web-based app for delirium prevention in LCFs and analyse its feasibility and usability. Methods The app was developed based on the validity of the AI prediction model algorithm. A total of 173 participants were selected from LCFs to participate in a study to determine the predictive risk factors for delerium. The app was developed in five phases: (1) the identification of risk factors and preventive intervention strategies from a review of evidence-based literature, (2) the iterative design of the app and components of delirium prevention, (3) the development of a delirium prediction algorithm and cloud platform, (4) a pilot test and validation conducted with 33 patients living in a LCF, and (5) an evaluation of the usability and feasibility of the app, completed by nurses (Main users). Results A web-based app was developed to predict high risk of delirium and apply preventive interventions accordingly. Moreover, its validity, usability, and feasibility were confirmed after app development. By employing machine learning, the app can predict the degree of delirium risk and issue a warning alarm. Therefore, it can be used to support clinical decision-making, help initiate the assessment of delirium, and assist in applying preventive interventions. Conclusions This web-based app is evidence-based and can be easily mobilised to support care for patients with delirium in LCFs. This app can improve the recognition of delirium and predict the degree of delirium risk, thereby helping develop initiatives for delirium prevention and providing interventions. Moreover, this app can be extended to predict various risk factors of LCF and apply preventive interventions. Its use can ultimately improve patient safety and quality of care. © 2022, The Author(s).1